smodels


Namesmodels JSON
Version 3.0.1 PyPI version JSON
download
home_pagehttp://smodels.github.io/
SummaryA tool for interpreting simplified-model results from the LHC
upload_time2024-10-31 16:12:22
maintainerNone
docs_urlNone
authorThe SModelS collaboration, smodels-users@lists.oeaw.ac.at Current members: Mohammad Mahdi Altakach, Sabine Kraml, Andre Lessa, Sahana Narashima, Timothee Pascal, Camila Ramos, Humberto Reyes-Gonzalez, Yoxara Villamizar, Wolfgang Waltenberger Previously involved in SModelS: Gael Alguero, Federico Ambrogi, Juhi Dutta, Jan Heisig, Charanjit K. Khosa, Suchita Kulkarni, Ursula Laa, Veronika Magerl, Wolfgang Magerl, Philipp Neuhuber, Doris Proschofsky, Jory Sonneveld, Michael Traub, Matthias Wolf, Alicia Wongel
requires_pythonNone
licenseGPLv3
keywords simplified models lhc bsm theories interpretation supersymmetry ueds
VCS
bugtrack_url
requirements No requirements were recorded.
Travis-CI No Travis.
coveralls test coverage No coveralls.
            .. image:: https://smodels.github.io/pics/banner.png

.. |PyPI version| image:: https://badge.fury.io/py/smodels.svg
   :target: https://badge.fury.io/py/smodels

.. |GitHub Project| image:: https://img.shields.io/badge/GitHub--blue?style=social&logo=GitHub
   :target: https://github.com/SModelS

.. |DOI| image:: https://zenodo.org/badge/DOI/10.5281/zenodo.1169739.svg
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.. |Docs| image:: https://img.shields.io/badge/docs-main-blue.svg                    
   :target: https://smodels.readthedocs.io

.. |Colab| image:: https://colab.research.google.com/assets/colab-badge.svg
   :target: https://colab.research.google.com/github/SModelS/tutorials/blob/main/index.ipynb

|GitHub Project| |PyPI version| |CodeFactor| |Colab| |Docs|

==============
SModelS v3
==============

**SModelS -- A tool for interpreting simplified-model results from the LHC.**

SModelS is an automatic, public tool for interpreting simplified-model results
from the LHC. It is based on a general procedure to decompose Beyond the
Standard Model (BSM) collider signatures into
Simplified Model Spectrum (SMS) topologies. Our method provides a way to cast
BSM predictions for the LHC in a model independent framework, which can be
directly confronted with the relevant experimental constraints.


Installation
============

For instructions on how to install SModelS, see
the section `Installation <http://smodels.readthedocs.io/en/latest/Installation.html>`_ of the `SModelS online manual`_.


Running SModelS
===============

SModelS provides a command-line tool (runSModelS.py) for the basic functionalities,
which can be executed as:

*./runSModelS.py -p <parameter file> -f <input file or directory> -o <output directory>*

For help instructions:

*./runSModelS.py -h*

An example file on how to call the SModelS libraries from your own
Python code can be found in *Example.py*.

Detailed explanations on how to use SModelS, including explanations of the
output, can be found in the section `Using SModelS <http://smodels.readthedocs.io/en/latest/RunningSModelS.html>`_ of the `SModelS online manual`_.

A few example input files are provided in the inputFiles folder and can be
used to test *runSModelS.py*.


Citation
========

If you use this software please cite the SModelS v1-v3 manuals, the original
SModelS publication, as well as the programs it makes use of.  For your
convenience, the relevant citations are provided in bibtex format in
`references.bib <https://github.com/SModelS/smodels/blob/main/references.bib>`_.

For citing the experimental analyses in the database, you can use
`database.bib <https://github.com/SModelS/smodels-database-release/blob/main/database.bib>`_.

.. _SModelS online manual: http://smodels.readthedocs.io/

            

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